Corrija o seguinte erro no script do google earth engine: Line 223: clipimageMask.reduceToVectors is not a function
Print apenas o resultado daquilo que precisa ser modificado. O Script: 

Map.setOptions('SATELLITE')////"ROADMAP", "SATELLITE", "HYBRID" or "TERRAIN"

var importedStudyArea = ee.FeatureCollection("users/maximoicmbio/UCs_Todas");

//Region of interest
var UC2 = importedStudyArea.filter(ee.Filter.eq('nome','Estacao_Ecologica_Serra_Geral_Do_Tocantins'));
var nomesUCs = ee.List(importedStudyArea.aggregate_array('nome'));
print('nomesUCs', nomesUCs);

//Buffer
var buffer = 10000;
var Region = UC2.geometry().buffer(buffer);

var mascaraOtto = ee.Image(100).toInt().clip(Region)//, 2023, 2024

var lista1 = ee.List([2019, 2020])

var lista2 = ee.List.sequence(1985, 2024)

var runFire = lista1.map(function(i){
  
i = ee.Number(i).toInt().format()

// Define time interval to composite scenes
  var date_start= i.cat("-01-01");
  var date_end= i.cat("-12-31");

// Define a function to scale the data and mask unwanted pixels.
function maskL457sr(image) {
  // Bit 0 - Fill
  // Bit 1 - Dilated Cloud
  // Bit 2 - Unused
  // Bit 3 - Cloud
  // Bit 4 - Cloud Shadow
  var qaMask = image.select('QA_PIXEL').bitwiseAnd(parseInt('11111', 2)).eq(0);
  //var saturationMask = image.select('QA_RADSAT').eq(0);

  // Apply the scaling factors to the appropriate bands.
  var opticalBands = image.select('Red', 'NIR', 'SWIR1', 'SWIR2').multiply(0.0000275).add(-0.2);
  //var thermalBand = image.select('ST_B.*').multiply(0.00341802).add(149.0);

  // Replace the original bands with the scaled ones and apply the masks.
  return image.addBands(opticalBands, null, true)
      //.addBands(thermalBand, null, true)
      .updateMask(qaMask)
      //.updateMask(saturationMask);
}

//_________________________________________________________________________

// Define function to prepare OLI images.
function prepOLI(img) {
  img = img.select([ 'SR_B4', 'SR_B5', 'SR_B6','SR_B7', 'QA_PIXEL'],[ 'Red', 'NIR', 'SWIR1','SWIR2', 'QA_PIXEL']);
  //img = applyScaleFactors(img);
  //img = prepSrL8(img);
  img = maskL457sr(img);
  //img = renameOLI(img);
  //img = addIndices(img);
  //img = addNBR(img);
  //img = addNDVI(img);
  //img = add_MIRBI(img);
  //img = add_NBR_mask(img);
  return ee.Image(img)//.copyProperties(img, img.propertyNames()))
  .set('data',  ee.Number.parse(img.date().format("YYYYMMdd")).toInt())
  //.set('anomes',  ee.Number.parse(img.date().format("YYYYMM")).toInt())
  //.set('year',  ee.Number.parse(img.date().format("YYYY")).toInt())
  .addBands(ee.Image.constant(ee.Number.parse(img.date().format("YYYYMMdd"))).toInt().rename('Date'))
  //.addBands(ee.Image.constant(ee.Number.parse(img.date().format("YYYYMM"))).toInt().rename('Months'))
  //.addBands(ee.Image.constant(ee.Number.parse(img.date().format("YYYY"))).toInt().rename('Years'));
  .addBands(img.normalizedDifference(['SWIR2', 'NIR']).rename('NBR'))
  .addBands(img.expression('10* float(b("' + 'SWIR2' + '"))/10000 - 9.8 * float( b("' + 'SWIR1' + '")) /10000 + 2').rename('MIRBI'))
}

// Define function to prepare ETM+ images.
function prepETM(img) {
  img = img.select([ 'SR_B3', 'SR_B4','SR_B5','SR_B7', 'QA_PIXEL'],[ 'Red', 'NIR', 'SWIR1','SWIR2','QA_PIXEL']);
  //img = applyScaleFactors(img);
  //img = prepSrL8(img);
  img = maskL457sr(img);
  //img = renameETM(img);
  //img = addIndices(img);
  //img = etm2oli(img);
  //img = addNBR(img);
  //img = addNDVI(img);
  //img = add_MIRBI(img);
  //img = add_NBR_mask(img);
  return ee.Image(img)//.copyProperties(img, img.propertyNames()))
  .set('data',  ee.Number.parse(img.date().format("YYYYMMdd")).toInt())
  //.set('anomes',  ee.Number.parse(img.date().format("YYYYMM")).toInt())
  //.set('year',  ee.Number.parse(img.date().format("YYYY")).toInt())
  .addBands(ee.Image.constant(ee.Number.parse(img.date().format("YYYYMMdd"))).toInt().rename('Date'))
  //.addBands(ee.Image.constant(ee.Number.parse(img.date().format("YYYYMM"))).toInt().rename('Months'))
  //.addBands(ee.Image.constant(ee.Number.parse(img.date().format("YYYY"))).toInt().rename('Years'));
  .addBands(img.normalizedDifference(['SWIR2', 'NIR']).rename('NBR'))
  .addBands(img.expression('10* float(b("' + 'SWIR2' + '"))/10000 - 9.8 * float( b("' + 'SWIR1' + '")) /10000 + 2').rename('MIRBI'))
}


// import collections
// landsat 5 - TM
  var L5coll = ee.ImageCollection('LANDSAT/LT05/C02/T1_L2') 
  .filterBounds(Region)
  .filterDate(date_start,date_end)
  .map(prepETM);

// landsat 7 - ETM
  var L7coll = ee.ImageCollection('LANDSAT/LE07/C02/T1_L2')
  .filterBounds(Region)
  .filterDate(date_start,date_end)
  .map(prepETM);
  
// landsat 8 - OLI
  var L8coll = ee.ImageCollection('LANDSAT/LC08/C02/T1_L2')
  .filterBounds(Region)
  .filterDate(date_start,date_end)
  .map(prepOLI);
  
// landsat 9 - OLI2
var L9coll = ee.ImageCollection('LANDSAT/LC09/C02/T1_L2')
  .filterBounds(Region)
  .filterDate(date_start,date_end)
  .map(prepOLI);

// merge collections 
  var image_collection_type = ee.ImageCollection(L5coll.merge(L7coll).merge(L8coll).merge(L9coll))

//_________________________________________________________________________

var NBR_Cicatrizes = function  (img) {
  //var NBR = img.addBands(img.normalizedDifference(['SWIR2', 'NIR']).rename('NBR1'))
  //var mirbi = img.expression('10* float(b("' + 'SWIR2' + '"))/10000 - 9.8 * float( b("' + 'SWIR1' + '")) /10000 + 2').rename('MIRBI');
  var greenestT = img.select('NBR');
  //var greenestT1 = img.select('Date')
  var greenestT2 = img.select('MIRBI');
  var BA_seed_NBR_MIRBI = greenestT.gte(0.045).or(greenestT2.gte(1.999954928883314))//1.99996346970886)).not()
  var BA_seed_MIRBI = BA_seed_NBR_MIRBI
  var MaskDates = img.updateMask(BA_seed_MIRBI)//.rename('Date2')
  return MaskDates//img.addBands(MaskDates)
};


var image_collection_type1 = image_collection_type
.map(NBR_Cicatrizes)
.select('Date')
.reduce(ee.Reducer.firstNonNull())
.updateMask(mascaraOtto)
.set('year', i);

var image_collection_type2 = image_collection_type
.qualityMosaic('NBR')
.updateMask(mascaraOtto)
.set('year', i);
  
  return [image_collection_type2, image_collection_type1]
  
});


var clipimage1 = ee.ImageCollection.fromImages(runFire.map(function(viz){
  return ee.List(viz).get(0);
}));

var clipimage2 = ee.ImageCollection.fromImages(runFire.map(function(viz){ 
  return ee.List(viz).get(1);
}));

var clipimage = clipimage1
//.select('SWIR2', 'NIR', 'Red')
.filter(ee.Filter.eq('year', '2020'))

var clipimageMask = clipimage2
.filter(ee.Filter.eq('year', '2020'))


var visParams = {
  min: 0.0,
  max: 0.5,
  bands: ['SWIR2', 'NIR', 'Red'],
};

Map.addLayer(clipimage, visParams, 'clipimage');

Map.addLayer(clipimageMask,{min:20200101,max:20201231,
  palette: 
['#FF0000','#FF7F00','#FFFF00', '#00FF00', '#0000FF', '#4B0082', '#9400D3'],
//['#9400D3','#4B0082','#0000FF', '#00FF00', '#FFFF00', '#FF7F00', '#FF0000']
},'Cicatrizes');


var vector = clipimageMask.reduceToVectors({
      geometry: Region,
      scale: 30,
      geometryType: 'polygon',
      eightConnected: false,
      labelProperty: 'label',
      crs: 'EPSG:4326',
      bestEffort: true,
      maxPixels: 1e13,
      tileScale: 16
    });

var vectorComPropriedades = vector.map(function(vectFeature) {
      var areas2 = ee.Image.pixelArea().divide(10000).reduceRegion({
        reducer: ee.Reducer.sum(),
        geometry: vectFeature.geometry(),
        scale: 30,
        maxPixels: 1e13,
      });
      return vectFeature.set(areas2)
    });

Export.table.toDrive({
  collection: vectorComPropriedades, 
  description: 'BA_L5789_UC_ANO', 
  folder: 'BA_UC',
  fileFormat:  "SHP"});
  
Export.image.toDrive({
  image: clipimage,
  description: "L5789_MaxComp_UC_ANO",
  folder: "BA_UC",
  fileFormat: 'GeoTIFF',
  region: Region,
  maxPixels: 1e13,
  crs: 'EPSG:4326',
  scale: 30,
  });