PIE-Engine APP：计算水体面积提取

/**
 * @Name    :   基于PIE-Engine的水体频率变化长时序遥感监测自动计算平台
 * @Time    :   2021/06/30
 * @Author  :   中国地质大学（武汉）水体频率小组
 * @Desc    :   基于水体指数或监督分类方法的水体频率计算
 * @Source  :   航天宏图第四届 “航天宏图杯”PIE软件二次开发大赛云开发组二等奖获奖作品
 */

//设定预定的的变量备用
var layerKey = null;
var roiKey = null;
var selectDates = ["2016-1-1", "2016-12-31"];
var selectCode = "";
var selectTag = "NDWI";
var selectcity = "wuhan";
var selectyear = "2018";
var selectThreshold = "";
var k = 0,
    y = 0;
var selectYZ = "随机序列作为验证样本"
//这里是将图层
var layerTF = [false, false, false, false, false, false];

////////////////////////////////////////////////对数据的预处理部分/////////////////////////////////////////////////
//获得感兴趣的研究区域
function getROI(cityname) {
    var ChinaCity = pie.FeatureCollection('user/pieadmin/ChinaCity');
    var roi = ChinaCity.filter(pie.Filter.eq('市', cityname)).first().geometry();
    Map.centerObject(roi, 8);
    roiKey = Map.addLayer(roi, { color: "#ff0000", fillColor: "#00000000" }, "roi");
    return roi;
}

//计算水体指数
function NDWI(image) {
    var ndwi = image.normalizedDifference(['B3', 'B5']).rename('NDWI');
    return ndwi.gt(pie.Number(selectThreshold));
};

function AWEI(image) {
    var awei = image.select(["B2", "B3", "B5", "B6", "B7"]).expression(
        'B2+2.5*B3-1.5*(B5+B6)-0.25*B7', {
            B2: image.select("B2"),
            B3: image.select("B3"),
            B5: image.select("B5"),
            B6: image.select("B6"),
            B7: image.select("B7"),
        }).rename('AWEI');
    return awei.gt(pie.Number(selectThreshold));
};

function MNDWI(image) {
    var mndwi = image.normalizedDifference(['B3', 'B6']).rename('mNDWI');
    return mndwi.gt(pie.Number(selectThreshold));
}

//训练样本波段范围0-5000，LC08/02/SR数据集范围0-50000，除以10处理
function divide10(image) {
    return imgd10 = image.divide(10);
}

//SR去云处理
function maskL8sr(image) {
    var qa = image.select('QA_PIXEL');
    var mask = qa.bitwiseAnd(1 << 3).eq(0)
        .and(qa.bitwiseAnd(1 << 4).eq(0))
        .and(qa.bitwiseAnd(1 << 5).eq(0));
    return image.updateMask(mask);
}

///////////////////////////////////////////////机器学习分类水体/////////////////////////////////////////
function Machinelearning(images, samcity, k) {
    // 添加训练样本
    var TrainingPoints = pie.FeatureCollection('user/pieadmin/' + samcity + "ALL");
    // 预测使用的波段
    var bands = ['B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'NDVI', 'mNDWI', 'AWEI'];
    // 分类标签
    var label = 'waterclass';
    //选择训练训练器
    switch (k) {
        case 0:
            var classifer = pie.Classifier.rTrees().train(TrainingPoints, label, bands);
            break;
        case 1:
            var classifer = pie.Classifier.normalBayes().train(TrainingPoints, label, bands);
            break;
        case 2:
            var classifer = pie.Classifier.svm().train(TrainingPoints, label, bands);
            break;
    }

    function water_index(img) {
        var image = img.select(["B2", "B3", "B4", "B5", "B6", "B7"]);
        var ndvi = image.normalizedDifference(['B5', 'B4']).rename('NDVI');
        var mndwi = image.normalizedDifference(['B3', 'B6']).rename('mNDWI');
        var awei = image.select(["B2", "B3", "B5", "B6", "B7"]).expression(
            'B2+2.5*B3-1.5*(B5+B6)-0.25*B7', {
                B2: image.select("B2"),
                B3: image.select("B3"),
                B5: image.select("B5"),
                B6: image.select("B6"),
                B7: image.select("B7"),
            }).rename('AWEI');
        return img.addBands(ndvi).addBands(mndwi).addBands(awei);
    }

    var image = images.map(water_index);
    var resultImage = image.map(function(image) {
        var Rfiamge = image.select(bands).classify(classifer);
        return Rfiamge;
    });
//随机序列的生成
    var sampleFeatureCollection = TrainingPoints.randomColumn('random');
    if (y == 0) var sampleTestingFeatures = sampleFeatureCollection.filter(pie.Filter.gt("random", 0.7));
    if (y == 1) var sampleTestingFeatures = pie.FeatureCollection('user/pieadmin/' + samcity + "ALL");
    var checkM = classifer.confusionMatrix();
    print("训练矩阵-ACC系数：", checkM.acc(), "训练矩阵-Kappa系数：", checkM.kappa());
    var predictResult = sampleTestingFeatures.classify(classifer, "classification");
    var errorM = predictResult.errorMatrix("waterclass", "classification")
    print("验证矩阵-ACC系数：", errorM.acc(), "验证矩阵-Kappa系数：", errorM.kappa());
    return resultImage;
}
//计算有效像元
function validPixel(image) {
    return image.select('B2').gte(0);
};
//计算水体频率并分类
function FrequencyC(roi, startDate, endDate, way, samcity) {
    l8_images = pie.ImageCollection("LC08/02/SR")
        .filterDate(startDate, endDate)
        .filterBounds(roi)
        .filter(pie.Filter.lt('cloud_cover', 30))
        .select(['B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'QA_PIXEL'])
        .map(maskL8sr);

    print("影像数量为：");
    print(l8_images.size());

    //计算有效像元个数
    var pixel_validNumber = l8_images.map(validPixel).sum().clip(roi);

    //分方法计算水体个数和水体频率
    var water_validNumber;
    if (way == "NDWI") {
        water_validNumber = l8_images.map(NDWI).sum().clip(roi);
        var waterFrequency = water_validNumber.divide(pixel_validNumber).rename('frequency');
    }
    if (way == "AWEI") {
        water_validNumber = l8_images.map(AWEI).sum().clip(roi);
        var waterFrequency = water_validNumber.divide(pixel_validNumber).rename('frequency');
    }
    if (way == "MNDWI") {
        water_validNumber = l8_images.map(MNDWI).sum().clip(roi);
        var waterFrequency = water_validNumber.divide(pixel_validNumber).rename('frequency');
    }
    if (way == "随机森林") {
        water_validNumber = Machinelearning(l8_images.map(divide10), samcity, 0).sum().clip(roi);
        var waterFrequency = water_validNumber.divide(pixel_validNumber).rename('frequency');
    }
    if (way == "正态贝叶斯") {
        water_validNumber = Machinelearning(l8_images.map(divide10), samcity, 1).sum().clip(roi);
        var waterFrequency = water_validNumber.divide(pixel_validNumber).rename('frequency');
    }
    if (way == "支持向量机") {
        water_validNumber = Machinelearning(l8_images.map(divide10), samcity, 2).sum().clip(roi);
        var waterFrequency = water_validNumber.divide(pixel_validNumber).rename('frequency');
    }
    var vis2 = {
        min: 0,
        max: 1,
        palette: ['ffffff', 'f8f8ff', '87cefa', '1e90ff', '4169e1', '000080']
    };
    var data = {
        title: "水体频率",
        colors: ["#ffffff", "#f0f8ff", "#add8e6", "#87ceeb", "#6495ed", "#4169e1", "#0000ff", "#0000cd", "#000080"],
        labels: ["0", "0.25", "0.5", "0.75"],
        step: 2
    };
    var style = {
        right: "150px",
        bottom: "10px",
        height: "70px",
        width: "350px"
    };
    var legend = ui.Legend(data, style);
    Map.addUI(legend);
    var PermanentWater = waterFrequency.gte(0.75).rename("waterclass");
    var mask1 = waterFrequency.gte(0.25);
    var mask2 = waterFrequency.lt(0.75);
    var SensonalWater = pie.ImageCollection.fromImages([mask1, mask2]).sum().eq(2).rename('waterclass');
    var Land = waterFrequency.lt(0.25).rename("waterclass");
    var MaskPS = waterFrequency.gte(0.25);
    Map.addLayer(waterFrequency.updateMask(MaskPS), vis2, '水体频率图层');
    //显示各水体类别的图层
    Map.addLayer(PermanentWater.setMaskValue(0), { uniqueValue: '1', palette: ['000080'] }, 'permanent waterbody', layerTF[3]);
    Map.addLayer(SensonalWater.setMaskValue(0), { uniqueValue: '1', palette: ['FF0000'] }, 'seasonal waterbody', layerTF[4]);
    Map.addLayer(Land.setMaskValue(0), { uniqueValue: '1', palette: ['FFFF00'] }, 'land', layerTF[5]);
    Map.addLayer(l8_images.mosaic().clip(roi), { min: 0, max: 30000, bands: ["B4", "B3", "B2"] }, 'B4/B3/B2', layerTF[0]);
    Map.addLayer(l8_images.mosaic().clip(roi), { min: 0, max: 30000, bands: ["B5", "B4", "B3"] }, 'B5/B4/B3', layerTF[1]);
    Map.addLayer(l8_images.mosaic().clip(roi), { min: 0, max: 30000, bands: ["B5", "B6", "B4"] }, 'B5/B6/B4', layerTF[2]); //432,543,564
    return waterFrequency;
}
///////////////////////////////////////////////UI设计部分/////////////////////////////////////////
var label1 = ui.Label("基于PIE-engine的水体频率变化长时序遥感监测自动计算平台", { "font-size": "20px" })
var label2 = ui.Label("一、区域地表水水体频率计算：", { "font-size": "18px" })
var label3 = ui.Label("请选择研究的时间范围，选择起始时间和终止时间(2013.07——现在数据可用)：", { "font-size": "15px" });
var label4 = ui.Label("请选择水体提取方法，目前包括指数法和监督分类法：", { "font-size": "15px" });
//选择研究区模块
var textBox1 = ui.TextBox({
    placeholder: "请输入行政市名字(XX市)",
    value: selectCode,
    onChange: function(value) {
        selectCode = value;
    },
    disabled: false
})
var textboxName1 = ui.Label("请设置研究区范围，区域类别为市级行政区划范围，如武汉市：", { "font-size": "15px" });
var textboxPanel1 = ui.Panel({
    widgets: [textboxName1, textBox1],
    layout: ui.Layout.flow("vertical")
});

//选择时间范围模块
var selectdateName = ui.Label("日期范围：", { "font-size": "15px" });
var dateSelect = ui.DateSelect({
    type: "daterange",
    placeholder: "请输入数值",
    value: selectDates,
    onChange: function(value) { selectDates[0] = value[0];
        selectDates[1] = value[1]; },
    disabled: false,
});
var selectdatePanel = ui.Panel({
    widgets: [selectdateName, dateSelect],
    layout: ui.Layout.flow("horizontal")
});

//选择提取水体方法模块
var select1 = ui.Select({
    items: ['AWEI', 'NDWI', "MNDWI", "随机森林", "正态贝叶斯", "支持向量机"],
    placeholder: "请选择",
    value: selectTag,
    multiple: false,
    onChange: function(value) {
        selectTag = value;
    }
})
var selectName = ui.Label("水体提取方法：", { "font-size": "15px" });
var selectPanel = ui.Panel({
    widgets: [selectName, select1],
    layout: ui.Layout.flow("horizontal")
});


//下一步按钮
var btn1 = ui.Button({
    label: "下一步",
    type: "success",
    onClick: clickBtn1,
    style: { left: "250px" }
});

//第一层界面
var panel = ui.Panel({
    widgets: [
        label1, label2,
        textboxPanel1,
        label3,
        selectdatePanel,
        label4,
        selectPanel,
        btn1
    ],
    style: {
        width: "350px",
        backgroundColor: "#fff"
    }
});

var panel1;

function clickBtn1() {
    print("选择的参数是：", "市名：" + selectCode, "时间范围：" + selectDates[0] + "_" + selectDates[1], "计算方法:" + selectTag);
    var label3 = ui.Label("选择的提取方法为指数法");
    var label4 = ui.Label("选择的提取方法为监督分类法");

    //选择阈值模块
    var textBox2 = ui.TextBox({
        placeholder: "阈值(推荐值:0-0.2)",
        value: selectThreshold,
        onChange: function(value) {
            selectThreshold = value;
        },
        disabled: false
    })
    var textboxName2 = ui.Label("请输入指数法计算阈值：", { "font-size": "13px" });
    var textboxPanel2 = ui.Panel({
        widgets: [textboxName2, textBox2],
        layout: ui.Layout.flow("horizontal")
    });

    //计算水体频率按钮
    var btn2 = ui.Button({
        label: "计算水体频率",
        type: "success",
        onClick: clickBtn2,
        style: { left: "50px" }
    });
    var btn2N = ui.Button({
        label: "上一步",
        onClick: function() { ui.root.add(panel);
            ui.root.remove(panel1); },
        style: { left: "25px" }
    });
    var btnPanel = ui.Panel({
        widgets: [btn2N, btn2],
        layout: ui.Layout.flow("horizontal")
    });
    //选择训练样本模块
    var selectF = ui.Select({
        items: ['wuhan', 'suzhou', "tianjin", "ALL"],
        placeholder: "请选择",
        value: selectcity,
        multiple: false,
        onChange: function(value) {
            selectcity = value;
        }
    })
    var selectCName = ui.Label("选择训练样本城市名：", { "font-size": "13px" });
    var selectFPanel = ui.Panel({
        widgets: [selectCName, selectF],
        layout: ui.Layout.flow("horizontal")
    });


    //选择允许显示的图册模块
    var ckboxName = ui.Label("请选择需要加载显示的图层：");
    var checkbox = ui.Checkbox({
        label: ["B4/B3/B2", "B5/B4/B3", "B5/B6/B4", "永久性水体", "季节性水体", "陆地"],
        value: [],
        disabled: [],
        onChange: function(value) {
            layerTF[0] = false;
            layerTF[1] = false;
            layerTF[2] = false;
            for (var i = 0; i < value.length; i++) {
                if (value[i] == "B4/B3/B2") { layerTF[0] = true; }
                if (value[i] == "B5/B4/B3") { layerTF[1] = true; }
                if (value[i] == "B5/B6/B4") { layerTF[2] = true; }
                if (value[i] == "永久性水体") { layerTF[3] = true; }
                if (value[i] == "季节性水体") { layerTF[4] = true; }
                if (value[i] == "陆地") { layerTF[5] = true; }
            }
        }
    });


    //选择为指数法的界面
    if (selectTag == "AWEI" || selectTag == "NDWI" || selectTag == "MNDWI") {
        panel1 = ui.Panel({
            widgets: [
                label3,
                textboxPanel2,
                ckboxName,
                checkbox,
                btnPanel
            ],
            style: {
                width: "350px",
                backgroundColor: "#fff"
            }
        });
        k = 0;

    }

    //选择为机器学习法的界面
    if (selectTag == "随机森林" || selectTag == "正态贝叶斯" || selectTag == "支持向量机") {
        panel1 = ui.Panel({
            widgets: [
                label4,
                selectFPanel,
                ckboxName,
                checkbox,
                btnPanel
            ],
            style: {
                width: "350px",
                backgroundColor: "#fff"
            }
        });
        k = 1;
    }
    ui.root.add(panel1);
    ui.root.remove(panel);
}

function clickBtn2() {
    var str = "";
    if (k == 0) { print("计算的阈值为：" + selectThreshold);
        str = "计算的阈值为：" + selectThreshold; }
    if (k == 1) { print("选择的分类器为:" + selectcity);
        str = "选择的分类器为:" + selectcity; }
    if (selectYZ == "随机序列作为验证样本") y = 0;
    if (selectYZ == "训练样本作为验证") y = 1;
    var roi = getROI(selectCode);
    var waterFrequency = FrequencyC(roi, selectDates[0], selectDates[1], selectTag, selectcity);
    var printlabel = ui.Label("用户已选的参数为：", { "font-size": "20px" });
    var printlabel1 = ui.Label("市名：" + selectCode);
    var printlabel2 = ui.Label("时间范围：" + selectDates[0] + "_" + selectDates[1]);
    var printlabel3 = ui.Label("计算方法:" + selectTag);
    var printlabel4 = ui.Label(str);
    var selectTag1 = "B4/B3/B2";
    var label5 = ui.Label("请用户选择需要下载的影像，包括原始影像和水体频率：", { "font-size": "18px" })

    function clickBtn3() {
        print("导出影像:" + selectTag1);

        function exportImageToDrive(image, region) { //导出影像
            Export.image({
                image: image,
                description: "ExportImage",
                region: region,
                scale: 30
            });
        }
        if (selectTag1 == "B4/B3/B2") {
            timages = pie.ImageCollection("LC08/02/SR")
                .filterDate(selectDates[0], selectDates[1])
                .filterBounds(roi)
                .filter(pie.Filter.lt('cloud_cover', 20))
                .select(['B4', 'B3', 'B2'])
                .map(maskL8sr).mosaic().clip(roi);
            exportImageToDrive(timages, roi);
        }
        if (selectTag1 == "水体频率影像") { exportImageToDrive(waterFrequency, roi); }
    }
    var select2 = ui.Select({
        items: ['B4/B3/B2', '水体频率影像'],
        placeholder: "请选择",
        value: selectTag1,
        multiple: false,
        onChange: function(value) { selectTag1 = value; }
    });
    var btn12 = ui.Button({
        label: "确定",
        type: "success",
        onClick: clickBtn3,
        style: { left: "0px" }
    });
    var selectName2 = ui.Label("输出影像：");
    var selectPanel1 = ui.Panel({
        widgets: [selectName2, select2, btn12],
        layout: ui.Layout.flow("horizontal")
    });
    var panel2 = ui.Panel({
        widgets: [printlabel, printlabel1, printlabel2, printlabel3, printlabel4, label5, selectPanel1],
        style: {
            width: "350px",
            backgroundColor: "#fff"
        }
    });
    ui.root.add(panel2);
    ui.root.remove(panel1);
}
ui.root.add(panel);